Some features don't land in Europe because US companies can't handle the amount of languages. For them it is English and maybe Spanish or Chinese because they don't care how heybmake money.
I think there's a ton of examples where this is true for lower level stuff like open source where you see the internals.
For commerical products it certainly exists too, for example in those cases where you know the product is built by one person or a small group of people who you absolutely know take extraordinary care to get all the details right, and it shows through as a really nice intangible feeling when you're using the product.
That (kind of rare to be honest) 'oh this is just really well done' feeling.
Platforms that are obviously vibe slop are almost entirely ignored by those that value quality.
If your product has that cheap stench of AI I'll never trust it, I'll instantly think the creators are chumps and I'll look for any alternative that doesn't have that stench.
You are right I forgot about that ! I think my point still stands - price per token is not decreasing for frontier capabilities, in fact it's increasing.
This only means the frontier is growing faster than the price is decreasing. It's just the sum of two separate tendencies, and has little predictive value. TBH, I'm ok with this tradeoff - higher capability at slightly higher cost is perfectly fine.
One interesting thing I found comparing OpenAI and Gemini image editing is - Gemini rejects anything involving a well known person. Anything. OpenAI is happy to edit and change every time I tried
I have a sideproject where I want to display standup comedies. I thought I could edit standup comedy posters with some AI to fit my design. Gemini straight up refuses to change any image of any standup comedy poster involving a well know human. OpenAI does not care and is happy to edit away
I don't know tbh. I've tried it on 10-20 various level of famous standups and Gemini refuses every time
Just for testing, I just tried this https://i.ytimg.com/vi/_KJdP4FLGTo/sddefault.jpg ("Redesign this image in a brutalist graphic design style"). Gemini refuses (api as well as UI), OpenAI does it
It seems like they're trying to follow local law. What a nightmare to have to manage all jurisdictions around such a product. Surprised it didn't kill image generation entirely.
Yea, especially when they know all that work will be completely pointless in a few years when open source / local models will be just as good and won't have any legal limitations, so people will be generating fake images of famous people like crazy with nothing stopping them
OpenAI wouldn't make me a Looney Tunes Roadrunner Martin Scorsese "Absolute Cinema" parody, but Gemini didn't blink about the trademark violation. Also, the output was really nice:
I think these pledges offload some of the risk onto Amazon/Oracle/etc
If Anthropic/OpenAI miss projections, infra providers can somewhat likely still turn around and sell it to the next guy or use it themselves. If they have more demand than expected (as Anthropic currently does), vcs will throw money at them and they can outbid the competition
If they built it themselves and missed projections it's a much more expensive mistake
It's just risk sharing. Infra providers take some of the risk and some of the upside
> If they built it themselves and missed projections it's a much more expensive mistake
Not if their pricing comes with multiyear commitments for reserved pricing. No doubt they get a huge volume discount but the advertised AWS reserved pricing is already enough for pay for a whole 8x HX00 pod plus the NVIDIA enterprise license plus the staff to manage it after only a one year commitment. On-demand pricing is significantly more expensive so they’re going to be boxed in by errors in capacity planning anyway (as has been happening the last few months).
The economics here are absurd unless you’re involved in a giant circular investment scheme to pump up valuations.
The pricing models that are published on AWS' website almost certainly have almost nothing to do with the pricing models that are discussed behind closed doors for a $100 billion commitment.
Of course not, but unless they’re getting the sweet heart deal of a lifetime from Amazon of all places, it’s still a hogwash. We’re talking about enough capital to build their own fab and a dozen datacenters*. This deal isn’t going to be buying existing capacity because that’s already stretched, it will be paying for new buildouts.
Afterwards Amazon will be milking the machines these commitments buy for nearly a decade. That tradeoff makes sense at a small scale (even up to $X00 million or even billions), but at $Y0 or $Z00 billion?
Color me skeptical. There are plenty of other side benefits like upgrading to the newest GPUs every few years, but again we’re talking about paying for new buildouts with upfront commitments anyway.
* obviously the timelines, scientific risk, and opportunity cost make this completely infeasible but that’s the scale we’re talking about. It’s a major industrial project on the scale of the thirty year space shuttle program (~$200 billion).
That’s just wrong. File reads, searches, compiler output, are the top input token consumers in my workflow. None of them can be removed. And they are the majority of my input tokens. That’s also why labs are trying to make 1M input work, and why compaction is so important to get right.
Regarding output - yes, but that wasn’t the topic in this thread. It’s just easier to argue with input tokens that price has gone up. I have a hunch the price for output will go up similarly, but can’t prove it. The jury’s out IMO: https://news.ycombinator.com/item?id=47816960
This has no bearing on my comment. The point is that a better model avoids dozens of prompts and tool calls by making fewer CORRECT tool calls, with the user needing no more prompts.
I’m surprised this is even a question; obviously a better prompter has the same properties and it’s not in dispute?
Or never. Like the majority of Pixel 10 on device AI features (image editing, magic cue).
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